{"title":"Dominant misconceptions and alluvial flows between Engineering and Physical Science students","authors":"Anna Chrysostomou, Alan S. Cornell, Wade Naylor","doi":"arxiv-2408.12083","DOIUrl":null,"url":null,"abstract":"In this article we assess the comprehension of physics concepts by Physical\nScience and Engineering students enrolled in their first semester at the\nUniversity of Johannesburg (UJ), South Africa ($2022$). We employ different\ngraphical measures to explore similarities and differences using the results of\nboth pre- and post-test data from the Force Concept Inventory assessment tool,\nfrom which we calculate dominant misconceptions (DMs) and gains. We also use\nalluvial diagrams to track the choices made by these two groups of students\nfrom pre- to post-test stages. In our analysis, we find that DMs results\nindicate that participating Engineering students outperformed Physical Science\nstudents on average. However, the same types of normalised DMs persist at the\npost-test level. This is very useful when tracking persistent misconceptions,\nwhere when using repeated measures and alluvial diagrams with smaller groups of\nstudents, we find that Physical Science students tend to make more chaotic\nchoices.","PeriodicalId":501565,"journal":{"name":"arXiv - PHYS - Physics Education","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Physics Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.12083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article we assess the comprehension of physics concepts by Physical
Science and Engineering students enrolled in their first semester at the
University of Johannesburg (UJ), South Africa ($2022$). We employ different
graphical measures to explore similarities and differences using the results of
both pre- and post-test data from the Force Concept Inventory assessment tool,
from which we calculate dominant misconceptions (DMs) and gains. We also use
alluvial diagrams to track the choices made by these two groups of students
from pre- to post-test stages. In our analysis, we find that DMs results
indicate that participating Engineering students outperformed Physical Science
students on average. However, the same types of normalised DMs persist at the
post-test level. This is very useful when tracking persistent misconceptions,
where when using repeated measures and alluvial diagrams with smaller groups of
students, we find that Physical Science students tend to make more chaotic
choices.